Key Responsibilities:

• Develop and optimize quantitative trading algorithms using Python, focusing on efficiency and scalability.
• Collaborate with quantitative researchers to translate complex models and strategies into robust, production-ready code.
• Implement machine learning techniques to analyze large datasets, identify patterns, and improve decision-making processes.
• Conduct performance analysis and backtesting of trading strategies to ensure reliability and effectiveness.
• Maintain and enhance existing trading systems, ensuring high availability and low latency.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Mathematics, Finance, or a related field.
• Strong programming skills in Python, with experience in data manipulation and algorithm development.
• Proven experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Solid understanding of quantitative finance concepts and trading strategies.
• Ability to analyze large datasets and apply statistical methods to derive insights.
• Excellent problem-solving skills and a collaborative mindset, with the ability to work in a fast-paced environment.

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